Infectious diseases, including COVID-19, are crucial public health issues and may lead to considerable fear among the general public and stigmatization of, and discrimination against, specific populations. This meta-analysis aimed to estimate the pooled prevalence of stigma in infectious disease epidemics. We systematically searched PubMed, PsycINFO, Embase, MEDLINE, Web of Science, and Cochrane databases since inception to June 08, 2021, and reported the prevalence of stigma towards people with infectious diseases including SARS, H1N1, MERS, Zika, Ebola, and COVID-19. A total of 50 eligible articles were included that contributed 51 estimates of prevalence in 92722 participants. The overall pooled prevalence of stigma across all populations was 34% [95% CI: 28−40%], including enacted stigma (36% [95% CI: 28−44%]) and perceived stigma (31% [95% CI: 22−40%]). The prevalence of stigma in patients, community population, and health care workers, was 38% [95% CI: 12− 65%], 36% [95% CI: 28−45%], and 30% [95% CI: 20−40%], respectively. The prevalence of stigma in participants from low- and middle-income countries was 37% [95% CI: 29−45%], which is higher than that from high-income countries (27% [95% CI: 18−36%]) though this difference was not statistically significant. A similar trend of prevalence of stigma was also observed in individuals with lower education (47% [95% CI: 23−71%]) compared to higher education level (33% [95% CI: 23−4%]). These findings indicate that stigma is a significant public health concern, and effective and comprehensive interventions are needed to counteract the damaging effects of the infodemics during infectious disease epidemics, including COVID-19, and reduce infectious disease-related stigma.

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MTV and TLG showed strong consistency with baseline serum CA19-9 level in better predicting OS and RFS, and might serve as surrogate markers for prediction of outcome in patients with resectable PDAC.

Objective: Antiangiogenesis therapy (AAT) has provided substantial benefits regarding improved outcomes and survival for suitable patients in clinical settings. Therefore, the early definition of therapeutic effects is urgently needed to guide cancer AAT. We aimed to optimize the early response monitoring and prediction of AAT efficacy, as indicated by the multi-targeted anti-angiogenic drug sunitinib in U87MG tumors, using noninvasive positron emission computed tomography (PET) molecular imaging strategies of multifactorial bioparameters.Methods: U87MG tumor mice were treated via intragastric injections of sunitinib (80 mg/kg) or vehicle for 7 consecutive days. Longitudinal MicroPET/CT scans with 18F-FDG, 18F-FMISO, 18F-ML-10 and 18F-Alfatide II were acquired to quantitatively measure metabolism, hypoxia, apoptosis and angiogenesis on days 0, 1, 3, 7 and 13 following therapy initiation. Tumor tissues from a dedicated group of mice were collected for immunohistochemical (IHC) analysis of key biomarkers (Glut-1, CA-IX, TUNEL, ανβ3 and CD31) at the time points of PET imaging. The tumor sizes and mouse weights were measured throughout the study. The tumor uptake (ID%/gmax), the ratios of the tumor/muscle (T/M) for each probe, and the tumor growth ratios (TGR) were calculated and used for statistical analyses of the differences and correlations.Results: Sunitinib successfully inhibited U87MG tumor growth with significant differences in the tumor size from day 9 after sunitinib treatment compared with the control group (P < 0.01). The uptakes of 18F-FMISO (reduced hypoxia), 18F-ML-10 (increased apoptosis) and 18F-Alfatide II (decreased angiogenesis) in the tumor lesions significantly changed during the early stage (days 1 to 3) of sunitinib treatment; however, the uptake of 18F-FDG (increased glucose metabolism) was significantly different during the late stage. The PET imaging data of each probe were all confirmed via ex vivo IHC of the relevant biomarkers. Notably, the PET imaging of 18F-Alfatide II and 18F-FMISO was significantly correlated (all P < 0.05) with TGR, whereas the imaging of 18F-FDG and 18F-ML-10 was not significantly correlated with TGR.Conclusion: Based on the tumor uptake of the PET probes and their correlations with MVD and TGR, 18F-Alfatide II PET may not only monitor the early response but also precisely predict the therapeutic efficacy of the multi-targeted, anti-angiogenic drug sunitinib in U87MG tumors. In conclusion, it is feasible to optimize the early response monitoring and efficacy prediction of cancer AAT using noninvasive PET molecular imaging strategies of multifactorial bioparameters, such as angiogenesis imaging with 18F-Alfatide II, which represents an RGD-based probe.